Abstract
We develop a grammatical error correction (GEC) system for German using a small gold GEC corpus augmented with edits extracted from Wikipedia revision history. We extend the automatic error annotation tool ERRANT (Bryant et al., 2017) for German and use it to analyze both gold GEC corrections and Wikipedia edits (Grundkiewicz and Junczys-Dowmunt, 2014) in order to select as additional training data Wikipedia edits containing grammatical corrections similar to those in the gold corpus. Using a multilayer convolutional encoder-decoder neural network GEC approach (Chollampatt and Ng, 2018), we evaluate the contribution of Wikipedia edits and find that carefully selected Wikipedia edits increase performance by over 5%.- Anthology ID:
- W18-6111
- Volume:
- Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text
- Month:
- November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
- Venue:
- WNUT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 79–84
- Language:
- URL:
- https://aclanthology.org/W18-6111
- DOI:
- 10.18653/v1/W18-6111
- Cite (ACL):
- Adriane Boyd. 2018. Using Wikipedia Edits in Low Resource Grammatical Error Correction. In Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, pages 79–84, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Using Wikipedia Edits in Low Resource Grammatical Error Correction (Boyd, WNUT 2018)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/W18-6111.pdf
- Code
- adrianeboyd/boyd-wnut2018